Second International Workshop on Symbolic-Neural Learning (SNL-2018)

July 5-6, 2018
Nagoya Congress Center (Nagoya, Japan)

Keynote Speakers:

Hang Li Toutiao Neural Symbolic Programming - A New Frontier of Artificial Intelligence
David McAllester Toyota Technological Institute at Chicago Universality in Deep Learning and Models of Computation
Tetsuya Ogata Waseda University Dynamical Integration of Language and Robot Actions by Deep Learning
Paul Smolensky Microsoft Research AI & Johns Hopkins University Vertical Integration of Neural and Symbolic Computation: Theory and Application
Richard Zemel University of Toronto Learning with Little Data

Invited Speakers:

Yuki Arase Osaka University Monolingual Phrase Alignment for Paraphrase Detection
Asako Kanezaki National Institute of Advanced Industrial Science and Technology, Japan Learning-based Visual Perception for Robot Navigation
Karen Livescu Toyota Technological Institute at Chicago Acoustic Word Embeddings
Michael Maire Toyota Technological Institute at Chicago Regularizing Deep Networks by Modeling and Predicting Label Structure
Makoto Miwa Toyota Technological Institute Neural Methods for Semantic Relation Extraction from Texts and Databases
Daichi Mochihashi Institute of Statistical Mathematics The Infinite Tree Hidden Markov Model
Naoaki Okazaki Tokyo Institute of Technology Bridging Knowledge and Text with Deep Neural Networks
Greg Shakhnarovich Toyota Technological Institute at Chicago Discriminability Loss for Learning to Generate Descriptive Image Captions
Hiroya Takamura National Institute of Advanced Industrial Science and Technology, Japan Describing Data with Text
Naonori Ueda NTT & RIKEN Simulation Based Machine Learning
Kazuyoshi Yoshii Kyoto University & RIKEN A New Approach to Deep Bayesian Learning for Audio, Speech, and Music Signal Analysis